Database Systems ( 資料庫系統 )

1. Database Systems(資料庫系統) September 27/28, 2006 Lecture #2

2. Course Administration • Office Hour: • Thur 2-3 • Can everyone get the textbook? • HW #1 will be on the course homepage later today • It is due 2 weeks from today. • Next week reading: • R&G Chapters 3 & 4.1~4.2

3. Chapter 2Introduction to Database Design

4. What is Design?

5. human shaping our (physical) environment with no precedent in nature to serve our needs and give meanings to our life

6. Shaping Nature (landscape design)

7. Serve our needs – high utility

8. Give us meaning - significance

9. Traditional design principle: form follows function

10. Some high style does not follow this principle (from philippe starck)

11. Digital environment never exists in nature How would you design it?

12. Scenario • Say if you are hired by iBeer Retailer as a computer consultant. • iBeer wants you to design its database system. • How to design it?

13. Database Design • Step 1: Requirements Analysis • What data to store in the database? • What application (e.g., queries, updates, ..) needs from the database? • Step 2: Conceptual Database Design • Come up with the design: Entity-Relation (ER) model • Sketch the design using pictures called entity-relationship diagrams. • Step 3: Logical Database Design • Implement the design: relational data model • Easy to map ER diagrams into the relational data model (CH 3).

14. name name addr ManfBy Beers Manfs Requirement Analysis • Requirement analysis: • The Beer retailer wants to keep track of • Beers on shelves • Beer manufacturers: [name & address] • Conceptual database design • ER diagram • Logical database design: • Relational model

15. Employees ER Model: Entity (‘Joe’: string) name (123: integer) ssn • Proposed by Peter Chen (BS NTU EE ‘68) in 1976. • Entity: A real-world object distinguishable from other objects (e.g., Joe). • An entity is described by a set of attributes. • Each attribute has a domain of possible values. • Entity Set: a collection of similar entities • Each entity in an entity set is uniquely identified by a key attribute. (Joe, Alice, ..)

16. ER Model: Relationship (5/2001) • Relationship: Association among two or more entities • Joe works in finance department. • A relationship can have descriptive attributes. • Joe has worked in finance department since 5/2001. • Relationship Set: Collection of similar relationships. since dname name budget did ssn (Joe) Works_In (finance dept) Employees Departments

17. Ternary Relationship since dname name budget did ssn Works_In Employees Departments (Joe) (finance dept) capacity address Locations (Taipei)

18. Roles in Relationship name ssn (Roles) Employees supervisor subordinate Reports_To

19. since dname Employees Key Constraints • Describe at most once (entitity) relationship • Manages relationship: each department has at most one manager (okay to have none). • One department can appear at most once in Manages relationship set, also calledone-to-many relation. name did budget ssn Departments Manages Finance Mary 3/3/93 Accounting Joe 2/2/92 Research Alice 3/1/92 Legal Peter

20. 1-to Many 1-to-1 Men Men Married Women Women Women Give Birth Babies More Key Constraints Many-to-Many Befriends

21. Participation Constraints • Describe all (entitity)participation relationship • Must every department have a manager? • If yes, this is a participation constraint • All Departments entities must participate in the Manages relationship set (total participation). since since name name dname dname ssn did did budget budget lot Departments Employees Manages Works_In since

22. Weak Entities • A weak entitycan be identified uniquely only by considering the key of another (owner) entity. • Pname = partial key • Owner entity set and weak entity set must participate in a one-to-many relationship set (one owner, many weak entities). • Weak entity set must have total participation in this identifying relationship set. (Alicia) (2) name cost pname age ssn (Hao) Policy Dependents Employees

23. ISA (`is a’) Hierarchies name ssn • As in C++ and OO languages, attributes are inherited from superclass. • A ISA B, every A entity is also considered to be a B entity. • Why using ISA? • Add descriptive attributesspecific (make sense) to a subclass. • Identify entities that make sense to a relationship (policy). superclass entity Employees hours_worked hourly_wages ISA contractid subclass entities Contract_Emps Hourly_Emps

24. ISA (`is a’) Constraints name ssn • Overlap constraints: Can Joe be an Hourly_Emps as well as a Contract_Emps entity? (Allowed/disallowed) • Covering constraints: Does every Employees entity also have to be an Hourly_Emps or a Contract_Emps entity?(Yes/no) Employees hours_worked hourly_wages ISA contractid Contract_Emps Hourly_Emps

25. Employees Aggregation name ssn • Create relationship set from relationship sets. • Aggregation: relationship set turns into an entity set • So that they can participate in (other) relationships. Monitors until since started_on dname pid pbudget did budget Sponsors Departments Projects

26. Design Guideline • Avoid redundancy. • Don’t use an entity set when an attribute will do. • Limit the use of weak entity sets.

27. Avoiding Redundancy • Redundancy occurs when we say the same thing in two different ways. • Redundancy is bad • wastes space • encourages inconsistency. • The two instances of the same fact may become inconsistent if we change one and forget to change the other instance.

28. Redundancy Example name name addr ManfBy Beers Manfs manf This design states the manufacturer of a beer twice: as an attribute and as a related entity.

29. Fix Redundancy name name addr ManfBy Beers Manfs This design gives the address of each manufacturer exactly once.

30. Example: Bad name manf manfAddr Beers • This design repeats the manufacturer’s address once for each beer. • Why is it bad? • Manf updates its address. • Loses the address if there are temporarily no beers for a manufacturer.

31. Entity Sets Versus Attributes • Modeling a concept with a new entity set should satisfy at least one of the following conditions: • It is more than the name of something; it has at least one nonkey attribute. or • It is the “many” in a many-one or many-many relationship.

32. Example: Okay name name addr ManfBy Beers Manfs • Manfs deserves to be an entity set because of the nonkey attribute addr. • Beers deserves to be an entity set because it is the “many” of the many-one relationship ManfBy.

33. Example: Beers Entity not Needed name name addr ManfBy Beers Manfs • Beers can be an attribute rather than an entity.

34. Example: Okay name manf Beers There is no need to make the manufacturer an entity set, because we record nothing about manufacturers besides their name.

35. Example: Bad name name ManfBy Beers Manfs Since the manufacturer is nothing but a name, and is not at the “many” end of any relationship, it should not be an entity set.

36. Don’t Overuse Weak Entity Sets • Beginning database designers often doubt that anything could be a key by itself. • They make all entity sets weak, supported by all other entity sets to which they are linked. • In reality, we usually create unique ID’s for entity sets. • Examples include social-security numbers, automobile VIN’s etc.

37. When Do We Need Weak Entity Sets? • The usual reason is that there is no global authority capable of creating unique ID’s. • Example: it is unlikely that there could be an agreement to assign unique player numbers across all football teams in the world.

38. Exercise 2.2 (R-G Book) A university database contains information about professors (identified by social security number) and courses (identified by courseid). Professors teach courses; each of the following situations concerns the Teaches relationship set. For each situation, draw an ER diagram that describes it. • Professors can teach the same course in several semesters, and each offering must be recorded.

39. Professors can teach the same course in several semesters, and only the most recent such offering needs to be recorded. • Every professor must teach some courses

40. Every professor teaches exactly one course (no more, no less) • Every professor teaches exactly one course (no more, no less), and every course must be taught by some professor

41. Exercise 2.3 (R-G Book) • Professors have an SSN, a name, an age, a rank, and a research specialty. • Projects have a project number, a sponsor name (e.g., NSF), a starting date, an ending date, and a budget.

42. Graduate students have an SSN, a name, an age, and a degree program • Each project is managed by exactly one professor (known as PI) • Each project is worked in by one or more professors (known as Co-PIs) • Each project is worked on by one or more graduate students (known as RAs)

43. When graduate students work on a project, a professor must supervise their work on the project. Graduate students can work on multiple projects, in which case they will have a potentially different supervisor for each one • Departments have a department number, a department name, and a main office. • Department has a professor (known as Chairman) who runs the department.

44. Professors work in one or more departments, and for each department that they work in, a time percentage is associated with their job • Graduate students have one major department in which they are working on their degree. • Each graduate student must have another, more senior graduate student as an advisor.

45. Summary • ER model is popular for conceptual design • Sketch the design of a database informally using pictures • Basic constructs in ER model: • entities, relationships, and attributes (of entities and relationships). • Some additional constructs: • weak entities, ISA hierarchies, and aggregation. • Several kinds of integrity constraints: • key constraints, participation constraints, and overlap/covering constraints for ISA hierarchies. • Design guideline in ER model

46. Ubicomp Project of the Week:Hyperdragging (SONY CSL, 1999) • How to bring human computer interaction (desktop PC) into the physical environment (just a bit)? • “Disappearing computing”